Enhanced-Precision LHSMC of Electrical Circuit Considering Low Discrepancy

The Monte-Carlo (MC) technique is very efficient solution for statistical problem. Various MC methods can easily be applied to statistical circuit performance analysis. Recently, as the number of process parameters and their impact, has increasingly affected circuit performance, a sufficient sample...

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Bibliographic Details
Published inJournal of semiconductor technology and science Vol. 15; no. 1; pp. 101 - 113
Main Authors Park, Eun-Suk, Oh, Deok-Keun, Kim, Ju-Ho
Format Journal Article
LanguageKorean
Published 2015
Subjects
latin hypercube sampling
low discrepancy sequence
Fast Monte Carlo
performance analysis
yield analysis
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Summary:The Monte-Carlo (MC) technique is very efficient solution for statistical problem. Various MC methods can easily be applied to statistical circuit performance analysis. Recently, as the number of process parameters and their impact, has increasingly affected circuit performance, a sufficient sample size is required in order to consider high dimensionality, profound nonlinearity, and stringent accuracy requirements. Also, it is important to identify the performance of circuit as soon as possible. In this paper, Fast MC method is proposed for efficient analysis of circuit performance. The proposed method analyzes performance using enhanced-precision Latin Hypercube Sampling Monte Carlo (LHSMC). To increase the accuracy of the analysis, we calculate the effective dimension for the low discrepancy value on critical parameters. This will guarantee a robust input vector for the critical parameters. Using a 90nm process parameter and OP-AMP, we verified the accuracy and reliability of the proposed method in comparison with the standard MC, LHS and Quasi Monte Carlo (QMC).
Bibliography:KISTI1.1003/JNL.JAKO201507964683430
ISSN:1598-1657